Data Engineer (AI Enablement)

3+ years building data systems (data modeling, ELT/ETL, Python + SQL). Experience with cloud object storage and relational databases. Hands-on with embeddings and vector databases (e.g., FAISS/pgvector/Milvus). Experience with document processing pipelines for RAG-style retrieval. Scalable pipeline experience supporting AI/ML/LLM use cases. Data structuring and manipulation expertise (JSON/Parquet/CSV normalization). Experience with orchestration/ops tools (Airflow/Prefect, CI/CD, logging, monitoring, secrets management).

Design and operate the vector database/search layer and document-chunking/embedding pipelines. Implement and maintain ELT/ETL for AI/ML/LLM workflows with validations and observability. Expose governed retrieval endpoints with permissions, metadata filters, and source citations. Normalize and transform JSON and other structured payloads. Align with product peers, design, data science, engineering, and commercial teams. Productionize MVPs with CI/CD, telemetry, and cost guardrails. Build monitoring, secrets management, access controls, and audit logging.